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421F39f091003a43dc7c22e364c The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-3/W8, 2019 Gi4DM 2019 – GeoInformation for Disaster Management, 3–6 September 2019, Prague, Czech Republic FLOOD ANALYSIS WITH REMOTE SENSING DATA – A CASE STUDY: MARITSA RIVER, EDIRNE A. F. Sunar1,* , N. Yagmur1 , A. Dervisoglu1 1 Istanbul Technical University, Civil Engineering Faculty, Geomatics Engineering Department, 34000, Maslak Istanbul, Turkey - (fsunar, yagmurn, adervisoglu)@itu.edu.tr KEY WORDS: Maritsa-Evros Basin, Flood, Remote Sensing, Sentinel 1/ 2 Data, GEE ABSTRACT: A flood, one of the most devastating natural disasters in the world, occurs when water inundates land that's normally dry. Although floods can develop in many ways, river floods (i.e. overflow by rivers or river banks) are the most common. Turkey is one of the flood-affected countries with its 20 main basins in 8 regions. One of the most aggrieved basins in Turkey is the Maritsa river basin in in Eastern Balkans, which also contains the natural border regions with Greece and Bulgaria. 65% of the Maritsa River basin, which originates from the Rila Mountains and joins the Arda and Tundzha rivers, is located in Bulgaria. When the melting snow flow or precipitation in the basin increases, the Maritsa River overflows from the slopes to the Edirne Plain and from time to time exceeds the capacity of the bed, causing floods. On the other hand, since the water level in the dams and reservoirs was kept at the highest level for production purposes, the flood repeat interval increased in the region, since 2000s. Today, it is possible to monitor and evaluate the damages of flood by obtaining very reliable information with space technology. Especially, microwave SAR images that can penetrate clouds, are of great importance in flood mapping because they provide immediate information on the extent of inundation and support the evaluation of property and environmental damages. In this study, rapid flood risk assessment in the region was performed using Landsat 8 and Sentinel 2 Normalized Difference Water Index (NDWI) time series images, and calibrated Sentinel 1 SAR images produced on Google Earth Engine (GEE) platform for 2015-2018 period. GEE is a cloud-based platform that facilitates access to high-performance computing resources to handle very large geographic data sets. The results were compared and verified using meteorological data, riverbed flow data, and digital media news. The results showed that the most affected areas were consistent with the highest measured flow rates and the magnitude of flood damages caused by two main causes in the basin (i.e. opening of shutters in Bulgarian dams or local excessive rainfall) was very different (approximately 8 times larger) from each other. 1. INTRODUCTION operations of the Bulgarian dams without causing economic loss (Sezen, 2007). Floods, which have serious environmental and social impacts worldwide, have been mostly caused by climate-related factors such as severe spring snowmelt and heavy rainfall in the last decade (CRED, 2015). Turkey is one of the countries affected by the floods with its 20 main basins in eight regions. One of the most aggrieved basins in Turkey is the Maritsa (Meriç in Turkish) river basin, located in Eastern Balkans containing the natural boundary regions with Greece and Bulgaria (INWEB, 2019). River floods in this basin where three rivers meet (biggest tributaries, Tundzha and Arda Rivers, joining in Maritsa in Edirne) are among the most common examples, due to excessive rainfall or snowmelt as well as uncontrolled water released from existing dams in Bulgaria and insufficient riverbed cross-sections. A significant number of reservoirs and cascades (about 2.2 billion m3 on the Maritsa and Tundzha Rivers and about 1 billion m3 on the Arda River in Bulgaria) have been built for irrigation and hydro- Figure 1. Trans-boundary Maritsa river basin and reservoirs electricity production (Figure 1). After 1994, with the (Yildiz, 2011). privatization of dams and hydroelectric power generation, the To prevent natural hazards such as flood, geo-information water level in the reservoirs was kept at the highest level for technologies (i.e. remote sensing and GIS) are used as an production purposes and the flood recurrence interval increased effective tool for risk assessment and hazard management, after this date (Yildiz, 2011). However, uncontrolled water providing a synoptic view and faster analysis than conventional released from existing dams directly overflows on the Maritsa surveying methods. Remote sensing systems with both passive River, causing serious transboundary floods in Edirne. Research optical sensors and active microwave sensors are often used for studies have shown that, especially after 2005, floods, occurred flood mapping and offer different levels of capacity and very often, can be prevented with proper implementations and accuracy (Shen et. al., 2019) (Figure 2). However, since the * Corresponding author This contribution has been peer-reviewed. 497 https://doi.org/10.5194/isprs-archives-XLII-3-W8-497-2019 | © Authors 2019. CC BY 4.0 License. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-3/W8, 2019 Gi4DM 2019 – GeoInformation for Disaster Management, 3–6 September 2019, Prague, Czech Republic validity of optical observations is limited by clouds, which are study, the period of 2015-2018 was taken into consideration common during flood events, microwave SAR systems are according to the operational dates of Sentinel 2 satellites. preferred providing more efficient analysis due to their penetration capabilities through the atmosphere (Shen et. al., 2019). Figure 2. Example of satellite dataset used for the latest flood of March 25, 2018. This study contributes to the application of cloud computing Google Earth Engine (GEE) and its potential for flood monitoring and mapping. Recently, GEE is being used for environmental data analysis that can determine important parameters from different satellite time series images. In this study, GEE was used to assess potential flood damage by visualizing and plotting the multi-temporal Landsat/Sentinel 2 NDWI and calibrated Sentinel 1 dB values in time series graphs. The findings were used to assess whether the increase in Figure 3. Map of the study area. flood frequency in the region was due to climate change or improper management of Bulgarian dams, together with Landsat 8 Sentinel 2 Sentinel 1 Satellite ancillary data. (optical) (optical) (SAR) C band 2. STUDY AREA & DATA USED Spectral 9 Bands 12 Bands (HH,HV,VH, (µm) (0.433-2.30) (0.443-2.20) The Maritsa river basin, is one of the major river systems VV) located in the eastern Balkans, with a total length of 550 km and B1-5,7.9: 30 m B2,3,4,8:10 m a total catchment area of 39,000 km2 (Figure 1) (INWEB, B5,6,7,8a, 2019). The city of Edirne, located in the North West region of Spatial (m) B6: 60 m 5 x 20 m 11,12 : 20 m Turkey, lies at the junction of the Tundzha, Arda and Maritsa rivers, near the borders of Greece and Bulgaria. The area of B8: 15 m B1,9,10: 60 m 44544.78 hectares covering Edirne Center was selected as the Radiometric 6 bit 12 bit 10 bit study area (Figure 3). Since 1571, Edirne city center has Temporal 16 days 10 days 12 days witnessed the most recorded floods resulting significant Resolutions negative environmental and economic impacts with a wide Table 1. The characteristics of the satellite data used variety of consequences from local to national scales (Turoglu (Url-1, Url-2). & Uludag, 2010). Meteorological data and flow measurements were also used as anchillary data in the analysis. Precipitation values and flow Landsat 8 OLI MSI and Sentinel 2 MSI, which are free optical data were obtained from Edirne Meteorological Station and 5 data since 2013 and 2015, were used as a satellite data set different flow observation stations, respectively. Research (Table 1). In addition to optical data, Sentinel 1 SAR data, shows that the discharge in Edirne city center should not exceed which has been free microwave satellite data since 2014, was 1000 m3/s, otherwise it causes flooding. When the maximum used for flood mapping due to its capability of capturing the flow values taken from the measurement station in Edirne center images day/night, irrespective of the weather conditions. In this This contribution has been peer-reviewed. 498 https://doi.org/10.5194/isprs-archives-XLII-3-W8-497-2019 | © Authors 2019. CC BY 4.0 License. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-3/W8, 2019 Gi4DM 2019 – GeoInformation for Disaster Management, 3–6 September 2019, Prague, Czech Republic between 1982 - 2015 are examined; especially after the 2000s, 4. RESULTS it is seen that the critical flow threshold is often exceeded (Url- 3) (Figure 4). 4.1. Optical data analysis Optical Landsat 8 and Sentinel 2 images were selected from the GEE archive for 2015 - 2018 by filtering with a percentage of cloud coverage of less than 10%. In this context, 52 (from 157) and 145 (from 408) images were used for Landsat and Sentinel 2 satellites, respectively. Then, NDWI time series for this area were created (Figure 5). Figure 4. Maximum flow values of Maritsa River measured by DSI between 1982-2015 (Url-3). 3. METHODOLOGY To evaluate the flooding occurance and mapping, the following image processing steps were applied. - Normalized Difference Water Index (NDWI) NDWI is a widely used remote sensing-derived index to monitor changes related to water content (water level or change in water level ― e.g. flooding) in water bodies. NDWI uses Green and Near-infrared bands of the satellite images to delineate and enhance open water features (Eq. 1) (McFeeters, 1996).
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